Identifying nucleating agents using machine learning
AssigneeGoogle Inc.
InventorsMuratahan Aykol, Ekin Dogus Cubuk
Life of this patent
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Abstract
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a nucleating agent for synthesis of a target material. According to one aspect, a method comprises: receiving data identifying a target material; generating an embedding of the target material in a latent space using an embedding machine learning model; and selecting one or more nucleating agents for the target material, from a set of candidate nucleating agents, based at least in part on the embedding of the target material in the latent space.
Claims20
A method performed by one or more computers, the method comprising:
- receiving data identifying a target material;
- generating an embedding of the target material in a latent space using an embedding machine learning model;
- and
- selecting one or more nucleating agents for the target material, from a set of candidate nucleating agents, based at least in part on the embedding of the target material in the latent space.
A system comprising:
- one or more computers;
- and
- one or more storage devices communicatively coupled to the one or more computers, wherein the one or more storage devices store instructions that, when executed by the one or more computers, cause the one or more computers to perform operations comprising:
- receiving data identifying a target material;
- generating an embedding of the target material in a latent space using an embedding machine learning model;
- and
- selecting one or more nucleating agents for the target material, from a set of candidate nucleating agents, based at least in part on the embedding of the target material in the latent space.
One or more non-transitory computer storage media storing instructions that when executed by one or more computers cause the one or more computers to perform operations comprising:
- receiving data identifying a target material;
- generating an embedding of the target material in a latent space using an embedding machine learning model;
- and
- selecting one or more nucleating agents for the target material, from a set of candidate nucleating agents, based at least in part on the embedding of the target material in the latent space.
Dependencies are inferred from the claim text.